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At least 73 records · Page 4

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Interplay between disorder, local relaxation, and collective behavior for an ensemble of emitters outside versus inside a cavity

The interplay between collective optical response and molecular static and dynamic disorder is studied using simple effective Hamiltonians for an ensemble of two-level emitters inside and outside a single-mode cavity. We model environmental disorder by randomly modulating the molecular transition frequencies and the coupling between the emitters and the electromagnetic field. We also consider the effects of intermolecular interactions and orientational disorder. We investigate how these effects lead to new features in the steady-state absorption (outside the cavity), transmission spectra (inside the cavity), and the yield of local molecular processes such as a unimolecular reaction. Outside the cavity, the collective behavior is manifested in the linewidth of the steady-state absorption, the emission spectrum, and the local chemical yield. Inside the cavity, however, the collective behavior primarily determines the Rabi splitting. The effects of intermolecular interactions under orientational disorder are also studied. For the most part, for all types of disorder, if we increase disorder, we find a reduction in the collective nature of the molecular response (smaller effective N) and therefore the Rabi splitting contraction occurs with orientational disorder. Furthermore, we find that static disorder is more destructive to collective behavior than dynamic disorder.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2024

Characteristic terahertz emissions induced by optically excited collective orbital modes

Here, we study the generation of collective orbital modes, their evolution, and the characteristic nonlinear optical response induced by them in a photoinduced orbital-ordered correlated oxide using real-time simulations based on an interacting multiband tight-binding (TB) model. The d-d optical transitions under femtoseconds light-pulse in an orbital-ordered state excite collective orbital modes, also known as “orbitons”. Consistently incorporating electronic interactions and the interplay between charge, spin, and lattice degrees of freedom in the TB-model provides a clearer understanding of how these factors influence the generation and evolution of collective orbital modes. The dynamics of Jahn-Teller vibrational modes in the photoinduced state modify the intersite orbital interaction, which further amplifies these orbital modes. In the presence of weak ferroelectricity, the excitation of collective orbital modes induces a strong THz oscillatory photocurrent, which is long-lived. This suggests an alternative way to experimentally detect low-energy collective modes through THz-emission studies in the photoinduced state. Our study also elucidates that quasiparticle dynamics in improper ferroelectric oxides can be exploited to achieve highly interesting and nontrivial optoelectronic properties.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Entanglement and many-body effects in collective neutrino oscillations

Collective neutrino oscillations play a crucial role in transporting lepton flavor in astrophysical settings, such as supernovae, where the neutrino density is large. In this regime, neutrino-neutrino interactions are important and simulations in the mean-field approximation show evidence for collective oscillations occurring at timescales much shorter than those associated with vacuum oscillations. In this work, we study the out-of-equilibrium dynamics of a corresponding spin model using matrix product states and show how collective bipolar oscillations can be triggered by many-body correlations if appropriate initial conditions are present. We find entanglement entropies scaling at most logarithmically in the system size suggesting that classical tensor network methods could be efficient in describing collective neutrino dynamics more generally. These observation provide a clear path forward, not only to increase the accuracy of current simulations, but also to elucidate the mechanism behind collective flavor oscillations without resorting to the mean-field approximation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Collective coordinate fix in the path integral

Collective coordinates are frequently employed in path integrals to manage divergences caused by fluctuations around saddle points that align with classical symmetries. These coordinates parametrize a manifold of zero modes and more broadly provide judicious coordinates on the space of fields. However, changing from local coordinates around a saddle point to more global collective coordinates is remarkably subtle. The main complication is that the mapping from local coordinates to collective coordinates is generically multivalued. Consequently one is forced to either restrict the domain of path integral in a delicate way, or otherwise correct for the multivaluedness by dividing the path integral by certain intersection numbers. We provide a careful treatment of how to fix collective coordinates while accounting for these intersection numbers, and then demonstrate the importance of the fix for free theories. We also provide a detailed study of the fix for interacting theories and show that the contributions of higher intersections to the path integral can be nonperturbatively suppressed. Using a variety of examples ranging from single-particle quantum mechanics to quantum field theory, we explain and resolve various pitfalls in the implementation of collective coordinates. Published by the American Physical Society 2024

Bhattacharya, Arindam (ORCID:0000000244578926)↗

DOE OSTI2020

Nonuniform Charge Collection in SiOx-Based Passivated-Contact Silicon Solar Cells

In this contribution, we report on the charge-collection characteristics of silicon photovoltaic devices using passivated contacts based on the c-Si/SiO x /poly-Si structure. Using electron-beam induced current (EBIC) imaging in plan-view and cross-section orientations, we find that charge collection in a device with a 1.5-nm-thick SiO x layer is fairly uniform in the p-n junction region and does not appear to be influenced by pyramidal surface texture. In contrast, a device with a 2.2-nm-thick oxide layer shows significant spatial variation in the charge-collection signal. The apexes of the pyramids exhibit reduced EBIC signal whereas the valleys between adjacent pyramids show the strongest collection. Our results indicate that charge collection in c-Si/SiO x /poly-Si structures can be influenced by both the properties of the SiO x layer and surface texture.

14 SOLAR ENERGY↗

DOE OSTI2019

Comparison of Sensitive Volumes Associated with Ion-and Laser-Induced Charge Collection in an Epitaxial Silicon Diode

A sensitive volume is developed using pulsed laser-induced collected charge for two bias conditions in an epitaxial silicon diode. These sensitive volumes show good agreement with experimental two photon absorption laser-induced collected charge at a variety of focal positions and pulse energies. When compared to ion-induced collected charge, the laser-based sensitive volume over predicts the experimental collected charge at low bias and agrees at high bias. Here, a sensitive volume based on ion-induced collected charge adequately describes the ion experimental results at both biases. Differences in the amount of potential modulation explain the differences between the ion-and laser-based sensitive volumes at the lower bias. Truncation of potential modulation by the highly doped substrate at the higher bias results in similar sensitive volumes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

WiP Abstract: Edge-Based Privacy of Naturalistic Driving Data Collection

Collecting large driving datasets is important for data-driven transportation research and studied in naturalistic driving [3]. Due to the standard implementation of a Controller Area Network (CAN) bus for a vehicle’s inter-module communication, many off-the-shelf devices can easily transform a vehicle into a rich data collection utility [2]. Vehicles with Adaptive Cruise Control (ACC) are an example of a feature resulting in emergent traffic behavior when scaled [4]. While these utilities were designed with particular data use cases, data may be publicly shared to benefit other researchers through online tools like CyVerse [1]. However, such data should only be shared when any private information is removed. This private information may exist as a set of GPS coordinates, since the start and end points of a trip may designate a driver’s place of residence or work. When considering larger continuously-collected data sets with a focus on naturalistic driving, many drivers are needed to make data collection feasible. Removal of private information becomes much more of a challenge since every driver may uniquely define their geographic privacy. This project aims to build upon the foundation of libpanda [2] by adding features of edge-based data privacy enforcement. In it’s current form, libpanda uses a GPS in conjunction with a CAN interface to record data. Libpanda feature s a set of startup and shutdown scripts to perform automatic data collection and upload. With additional support hardware on a Raspberry Pi, the Pi can maintain power on vehicle shutdown to automatically upload data before shutdown.

Bunting, Matt↗

DOE OSTI2023

Multisensor Agile Adaptive Sampling (MAAS): A Methodology to Collect Radar Observations of Convective Cell Life Cycle

Abstract Multisensor Agile Adaptive Sampling (MAAS), a smart sensing framework, was adapted to increase the likelihood of observing the vertical structure (with little to no gaps), spatial variability (at subkilometer scale), and temporal evolution (at ∼2-min resolution) of convective cells. This adaptation of MAAS guided two mechanically scanning C-band radars (CSAPR2 and CHIVO) by automatically analyzing the latest NEXRAD data to identify, characterize, track, and nowcast the location of all convective cells forming in the Houston domain. MAAS used either a list of predetermined rules or real-time user input to select a convective cell to be tracked and sampled by the C-band radars. The CSAPR2 tracking radar was first tasked to collect three sector plan position indicator (PPI) scans toward the selected cell. Edge computer processing of the PPI scans was used to identify additional targets within the selected cell. In less than 2 min, both the CSAPR2 and CHIVO radars were able to collect bundles of three to six range–height indicator (RHI) scans toward different targets of interest within the selected cell. Bundles were successively collected along the path of cell advection for as long as the cell met a predetermined set of criteria. Between 1 June and 30 September 2022 over 315 000 vertical cross-section observations were collected by the C-band radars through ∼1300 unique isolated convective cells, most of which were observed for over 15 min of their life cycle. To the best of our knowledge, this dataset, collected primarily through automatic means, constitutes the largest dataset of its kind.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Evaluation of genetic diversity, agronomic traits, and anthracnose resistance in the NPGS Sudan Sorghum Core collection

The United States Department of Agriculture (USDA) National Plant Germplasm System (NPGS) sorghum core collection contains 3011 accessions randomly selected from 77 countries. Genomic and phenotypic characterization of this core collection is necessary to encourage and facilitate its utilization in breeding programs and to improve conservation efforts. In this study, we examined the genome sequences of 318 accessions belonging to the NPGS Sudan sorghum core set, and characterized their agronomic traits and anthracnose resistance response. We identified 183,144 single nucleotide polymorphisms (SNPs) located within or in proximity of 25,124 annotated genes using the genotyping-by-sequencing (GBS) approach. The core collection was genetically highly diverse, with an average pairwise genetic distance of 0.76 among accessions. Population structure and cluster analysis revealed five ancestral populations within the Sudan core set, with moderate to high level of genetic differentiation. In total, 171 accessions (54%) were assigned to one of these populations, which covered 96% of the total genomic variation. Genome scan based on Tajima’s D values revealed two populations under balancing selection. Phenotypic analysis showed differences in agronomic traits among the populations, suggesting that these populations belong to different ecogeographical regions. A total of 55 accessions were resistant to anthracnose; these accessions could represent multiple resistance sources. Genome-wide association study based on fixed and random model Circulating Probability (farmCPU) identified genomic regions associated with plant height, flowering time, panicle length and diameter, and anthracnose resistance response. Integrated analysis of the Sudan core set and sorghum association panel indicated that a large portion of the genetic variation in the Sudan core set might be present in breeding programs but remains unexploited within some clusters of accessions. The NPGS Sudan core collection comprises genetically and phenotypically diverse germplasm with multiple anthracnose resistance sources. Population genomic analysis could be used to improve screening efforts and identify the most valuable germplasm for breeding programs. The new GBS data set generated in this study represents a novel genomic resource for plant breeders interested in mining the genetic diversity of the NPGS sorghum collection.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Hybridizing Classifiers and Collection Systems to Maximize Intelligence and Minimize Uncertainty in National Security Data Analytics Applications

There are numerous applications that combine data collected from sensors with machine-learning based classification models to predict the type of event or objects observed. Both the collection of the data itself and the classification models can be tuned for optimal performance, but we hypothesize that additional gains can be realized by jointly assessing both factors together. Through this research, we used a seismic event dataset and two neural network classification models that issued probabilistic predictions on each event to determine whether it was an earthquake or a quarry blast. Real world applications will have constraints on data collection, perhaps in terms of a budget for the number of sensors or on where, when, or how data can be collected. We mimicked such constraints by creating subnetworks of sensors with both size and locational constraints. We compare different methods of determining the set of sensors in each subnetwork in terms of their predictive accuracy and the number of events that they observe overall. Additionally, we take the classifiers into account, treating them both as black-box models and testing out various ways of combining predictions among models and among the set of sensors that observe any given event. We find that comparable overall performance can be seen with less than half the number of sensors in the full network. Additionally, a voting scheme that uses the average confidence across the sensors for a given event shows improved predictive accuracy across nearly all subnetworks. Lastly, locational constraints matter, but sometimes in unintuitive ways, as better-performing sensors may be chosen instead of the ones excluded based on location. This being a short-term research effort, we offer a lengthy discussion on interesting next-steps and ties to other ongoing research efforts that we did not have time to pursue. These include a detailed analysis of the subnetwork performance broken down by event type, specific location, and model confidence. This project also included a Campus Executive research partnership with Texas A&M University. Through this, we worked with a professor and student to study information gain for UAV routing. This was an alternative way of looking at the similar problem space that includes sensor operation for data collection and the resulting benefit to be gained from it. This work is described in an Appendix.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

General Analysis of Data Collected from DOE Lidar Buoy Deployments Off Virginia and New Jersey

Pacific Northwest National Laboratory (PNNL) operates two AXYS WindSentinel lidar buoys for the U.S. Department of Energy’s Wind Energy Technologies. The purpose of these buoys is to collect hub-height winds and supporting meteorological and oceanographic information to facilitate the development of offshore wind energy in the U.S. In general, each buoy is deployed for a year or more at a given location in order to capture at least a full annual cycle of weather conditions. The initial deployment for one buoy was off the coast of Virginia beginning in 2015, and the other buoy was first deployed off the coast of New Jersey beginning in 2016. Over the last two years, PNNL has had an opportunity to analyze the data collected during these first two deployments. This report describes a substantial analysis of data collected by the two lidar buoys operated off the coasts of Virginia and New Jersey. The centerpiece instrument for each buoy as deployed off Virginia and New Jersey is a lidar system, which is designed to measure the horizontal wind vector from approximately 40 m to 200 m above the sea surface with vertical resolution of 40 m. Since the initial deployments, the original lidars have been replaced with more powerful Leosphere 866 v2 systems. The analyses in this report will apply to the original Vindicator systems. In addition to the wind profiles from the lidars, the buoys collect near-surface measurements of wind speed and direction, air temperature, relative humidity, barometric pressure, and solar irradiance. Oceanographic variables measured include the two-dimensional wave spectrum, water temperature and conductivity, and ocean current vectors to a depth of 90 m. An assessment of overall data recovery and a basic analysis of the data collected was provided in a previous report This report substantially extends that analysis. The various sections describe the development and application of an inertial measurement unit (IMU) data recovery scheme for the New Jersey deployment; a climatological analysis of winds at hub height and at the surface together with thermodynamic variables measured at the surface for the full deployment periods; an analysis of oceanographic observations describe sea state; the development of a refinement for NOAA’s WaveWatch III model to allow its application to near-shore areas; a basic climatology of ocean currents observed from the buoys; an analysis of observed winds in the framework of Monin-Obukhov Similarity Theory; and the development and evaluation of techniques to extract turbulence intensity and turbulence kinetic energy from the lidars. The analyses contained in this report provide a great deal of new information about offshore conditions on the U.S. East Coast. In addition, the experience gained will inform both configurations and analysis of data from future deployments of these lidar buoy systems.

17 WIND ENERGY↗

DOE OSTI2022

2021 Results for Avian Monitoring of Inorganic and Organic Element Concentrations in Passerine Eggs and Nestlings Collected from Technical Area 16 Burn Grounds, Technical Area 36 Minie, and Technical Area 39 Point 6 at Los Alamos National Laboratory (Rev. 2)

In 2021, non-viable avian eggs and one nestling were opportunistically collected at Los Alamos National Laboratory (LANL) near open detonation sites located at Technical Area (TA) 16 burn grounds and TA-36 Minie. Similar to previous years, nestboxes were monitored at TA-39 Point 6, however, no avian samples were available for opportunistic collection. Samples were evaluated for inorganic elements (mostly metals), dioxins, and furans. One ash-throated flycatcher (Myiarchus cinerascens) egg sample was collected from TA-16 burn grounds. One ash-throated flycatcher and one mountain bluebird (Sialia currucoides) egg sample and one deceased western bluebird (Sialia mexicana) nestling sample were collected from TA-36 Minie. Concentrations of inorganic elements observed in this study were compared with the regional statistical reference level (RSRL) which is the upper-level bounds of background concentrations (mean + three standard deviations = 99% confidence interval). Several inorganic elements were not detected in avian eggs. Most inorganic elements detected were below the RSRL and all were the lowest observable adverse effect level (LOAEL), when available. The nestling collected from TA-36 did not contain detectable concentrations of dioxin or furan congeners. These data suggest that inorganic and organic element concentrations in eggs and nestlings are not of ecological concern. More data are needed to make a robust assessment and to evaluate trends over time.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Collection of Aerosol Particles in a Single-Stage, High Gradient Magnetic Collector

The collection of aerosol particles that have magnetic components such as actinides, Co/Ni/Fe, brass, and alloys are of interest in the nuclear industry and for regulatory applications. The collection of these particles is important for monitoring and a number of collection approaches have been developed based on separations mechanisms including size, mass, electrical or thermal properties. In this work, we present the performance of a single-stage, high gradient magnetic collector with a nickel foam matrix for removing airborne magnetic particles. The collection efficiencies for two different particle size regimes and compositions (NaCl and Fe 3 O 4 below 200 nm and SiO 2 and Fe 3 O 4 at 1-2 μm) were measured to assess the performance of the magnetic collector. The high gradient magnetic collector did not remove nanosized magnetic Fe 3 O 4 particles any more effectively than non-magnetic NaCl particles. However, in the larger size range, the collector more efficiently removed Fe 3 O 4 particles compared to SiO 2 with a collection efficiency of 99% compared to 84% for SiO 2 . The removal mechanism could be attributed to both filtration and the high gradient magnetic field.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

2022 Results for Avian Monitoring of Inorganic Elements and Organic Chemical Concentrations in Passerine Eggs and Nestlings Collected from Technical Area 16 Burn Grounds, Technical Area 36 Minie, and Technical Area 39 Point 6 at Los Alamos National Laboratory

In 2022, nonviable avian eggs and one nestling were opportunistically collected at Los Alamos National Laboratory (LANL) near open detonation sites located at Technical Area (TA) 16 burn grounds, TA-36 Minie, and TA-39 Point 6. Samples were evaluated for inorganic elements (mostly metals) or per- and polyfluoroalkyl substances (PFAS). Three western bluebird (Sialia mexicana) egg samples were collected from TA-16 burn grounds. One deceased mountain bluebird (Sialia currucoides) nestling sample was collected from TA-36 Minie. One ash-throated flycatcher (Myiarchus cinerascens) egg sample was collected from TA-39 Point 6. Concentrations of inorganic elements (i.e., mostly metals) observed in this study were compared with the regional statistical reference level (RSRL), which is the upper-level bounds of background concentrations (mean + three standard deviations = 99% confidence interval). Several inorganic elements were not detected in avian eggs. All of the inorganic elements that were detected were below the RSRL and the lowest observable adverse effect level (LOAEL), when available. No PFAS compounds were detected in the mountain bluebird nestling sample collected from TA-36, and the majority of PFAS compounds were not detected in the western bluebird egg sample from TA-16. These data suggest that inorganic element and PFAS concentrations in eggs and nestlings are not of ecological concern. More data are needed to make a robust assessment and to evaluate trends over time.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Collective Energy Transport of Excitons in Two-dimensional Materials (Final Report)

The goal of this project is to explore collective behavior that exists in samples with large numbers of interacting particles. The behavior of these systems goes beyond the independent particle picture that is commonly used to describe a vast majority of solid–state phenomena, including the transport of quantized carriers of charge and heat in solids. While collective behavior gives rise to superconductivity at low temperatures, signatures of collective behaviors in both charge and heat transport appear at rather high temperatures in several recent studies of low–dimensional materials. One specific example of this collective behavior is the formation of excitons (i.e., bound electron–hole pairs), which is pronounced in two–dimensional (2D) materials such as transition metal dichalcogenides (TMDCs), with exciton binding energies exceeding the thermal energy at room temperature. In this project, we pursue, optical, electronic, thermal, and thermoelectric measurements to obtain unique insights into the unusual collective energy transport behaviors of excitons in 2D materials and heterostructures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2025

Field-Driven Out-of-Equilibrium Collective Patterns for Swarm Micro-Robotics

Soft robotics has been rapidly advancing, offering significant improvements over traditional rigid robotic systems through the use of compliant materials that enhance adaptability and interaction with the environment. However, current approaches face critical challenges, including the reliance on complex “top-down” fabrication techniques and the difficulty of wireless powering and control at the microscale. Swarm robotics introduces a paradigm shift, leveraging collective dynamics to achieve cooperative and adaptable behaviors among multiple robotic units. Inspired by nature, this “bottom-up” approach enables swarm robots to execute task-specific reconfigurations, enhancing flexibility and robustness. Field-driven active colloids emerge as a promising platform for swarm microrobotics, capable of self-propulsion and self-organization into dynamic collective patterns under external field excitation and manipulation. These systems mimic biologically inspired swarm behaviors, such as flocking and vortex formation, providing a versatile foundation for designing innovative swarm microrobots. Here, this review discusses the principles of electric and magnetic field-driven collective self-organization, focusing on the particle dynamics, the emergence of collective swarm patterns, and illustrative examples of functional swarm microrobots. It concludes with future perspectives on harnessing these systems for adaptive, scalable, and multifunctional microrobotic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2020

Identification of Collectible Items in the Rancor Microworld Simulator Compared to Full-scope Studies

Most studies collecting reliability data in human reliability analysis (HRA) have concentrated on research using full-scope simulators and actual operators. However, several researchers have found that there are challenges to collecting the variety of items as well as the amount of data needed to support HRA. As an opposite and complementing approach to the full-scope study, Idaho National Laboratory (INL) has developed a simplified simulator, i.e., Rancor Microworld, for generating HRA data based on student subjects. This paper aims to identify collectible items in Rancor Microworld versus full-scope simulators. In this paper, collectible items and their different analysis levels in Rancor Microworld are identified in comparison with full-scope simulators. Then, how to treat the items is suggested with experiment directions that will be treated in the future.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Effective field theories for collective excitations of atomic nuclei

Collective modes emerge as the relevant degrees of freedom that govern low-energy excitations of atomic nuclei. These modes—rotations, pairing rotations, and vibrations—are separated in energy from non-collective excitations, making it possible to describe them in the framework of effective field theory. Rotations and pairing rotations are the remnants of Nambu–Goldstone modes from the emergent breaking of rotational symmetry and phase symmetries in finite deformed and finite superfluid nuclei, respectively. The symmetry breaking severely constrains the structure of low-energy Lagrangians and thereby clarifies what is essential and simplifies the description. The approach via effective field theories exposes the essence of nuclear collective excitations and is defined with a breakdown scale in mind. This permits one to make systematic improvements and to estimate and quantify uncertainties. Effective field theories of collective excitations have been used to compute spectra, transition rates, and other matrix elements of interest. In particular, predictions of the nuclear matrix element for neutrinoless double beta decay then come with quantified uncertainties. This review summarizes these results and also compares the approach via effective field theories to well-known models and ab initio computations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗